Comparative Analysis Of AI Regression And Classification Models For Predicting House Damages İn Nepal: Proposed Architectures And Techniques

Abstract

This paper proposes a machine-learning model for earthquake prediction. Earthquakes are complex and unpredictable natural phenomena, making it challenging to predict them accurately. However, recent advances in machine learning techniques have shown promise in predicting earthquakes by analyzing various factors such as seismic activity, geospatial data, and weather patterns. In this study, we collected earthquake data from multiple sources and used it to train a machine-learning model. We evaluated the model's performance using accuracy, precision, and recall metrics. Our results demonstrate that our machine-learning model can accurately predict earthquakes with high precision and recall. The model has the potential to provide early warnings of earthquakes, which can help reduce the damage caused by these disasters. Overall, this study highlights the potential of machine learning in earthquake prediction and provides a roadmap for future research in this field.